Name
Abstract | ||
|---|---|---|
We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration-driven experimentation with state-of-the-art models and implements a broad set of tasks for probing, transfer learning, and multitask training experiments. jiant implements over 50 NLU tasks, including all GLUE and SuperGLUE benchmark tasks. We demonstrate that jiant reproduces published performance on a variety of tasks and models, including BERT and RoBERTa. jiant is available at https: // jiant. info. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.18653/v1/2020.acl-demos.15 | ACL (demo) |
DocType | Volume | Citations |
Conference | 2020.acl-demos | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yada Pruksachatkun | 1 | 8 | 1.81 |
| Philip Yeres | 2 | 0 | 0.34 |
| Haokun Liu | 3 | 1 | 3.40 |
| Jason Phang | 4 | 22 | 4.09 |
| Phu Mon Htut | 5 | 6 | 2.79 |
| Alex Wang | 6 | 71 | 5.27 |
| Ian Tenney | 7 | 4 | 3.79 |
| Samuel R. Bowman | 8 | 0 | 0.34 |